Distributed Computing

, Volume 5, Issue 2, pp 55–65 | Cite as

Optimal geometric algorithms for digitized images on fixed-size linear arrays and scan-line arrays

  • Hussein M. Alnuweiri
  • Viktor K. Prasanna
Article

Summary

Linear arrays are characterized by a small communication bandwidth and a large communication diameter rendering them unsuited to the implementation of global computations. This paper presents efficient data movement and partitioning techniques to overcome several shortcomings of linear arrays. These techniques are used to derive optimal parallel algorithms for several geometric problems onn×n images using a fixed-size linear array withp processors, where 1≤pn.O(n2/p) time solutions are presented for labeling connected image regions, computing the convex hull of each region, and computing nearest neighbors. Consequently, a linear array withn processors can solve several image problems inO(n) time which is the same time taken by a two dimensional mesh-connected computer withn2 processors. Limitations of linear arrays are analyzed by presenting a class of image problems which can be solved sequentially inO(n) 2 ) time, but require Ω(n2) time on a linear array, irrespective of the number of processors used and the partitioning of the input image among the processors. An alternate communication-efficient fixed-size organization withp processors is proposed to solve such problems inO(n2/p) time, for 1≤pn.

Key words

Linear arrays Image processing Optimal algorithms 

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References

  1. 1.
    Aho A, Hopcroft J, Ullman J: Design and analysis of computer algorithms. Addison Wesley, 1974.Google Scholar
  2. 2.
    Alnuweiri HM, Prasanna Kumar VK: Optimal image computations on reduced VLSI architectures. IEEE Trans Circuits Syst 36(10):1365–1375 (1989)CrossRefGoogle Scholar
  3. 3.
    Alnuweiri HM, Prasanna Kumar VK: Fast image labeling using local operators on mesh connected arrays. Proc Int Conf on Parallel Processing, 1989Google Scholar
  4. 4.
    Alnuweiri HM, Prasanna Kumar VK: Processor-time optimal parallel algorithms for digitized images on mesh-connected arrays. Algorithmica (to appear)Google Scholar
  5. 5.
    Annaratone M, Arnould E, Gross T, Kung HT, Lam M, Menzilcioglu O, Sarocky K, Webb JA: Warp architecture and implementation. Proc 13th Annu Int Symp on Computer Architecture, June 1986Google Scholar
  6. 6.
    Baudet G, Stevenson D: Optimal sorting algorithms for parallel computers. IEEE Trans Comput (C-27) (1978)Google Scholar
  7. 7.
    Doshi KA, Varman PJ: Optimal graph algorithms on a fixed-size linear array. IEEE Trans Comput (C-36) (1987)Google Scholar
  8. 8.
    Dyer C: A VLSI pyramid machine for hierarchical parallel image processing. Proc of IEEE Conf on Pattern Recognition and Image Processing, 1981Google Scholar
  9. 9.
    Fisher AI: Scan line array processors for image computations. Int Conf on Computer Architecture, 1986Google Scholar
  10. 10.
    Graham RL: An efficient algorithm for determining the convex hull of a finite planar set. Inf Process Lett 1:132–133 (1972)CrossRefGoogle Scholar
  11. 11.
    Hinkle EB, Sanz JLC, Jain AK, Petkovic D:P 3 E new life for projection-based image processing. J Parallel Distrib Comput 4:45–87 (1987)CrossRefGoogle Scholar
  12. 12.
    Ja'Ja' J, Prasanna Kumar VK: Information transfer in distributed computing with applications to VLSI. J ACM 31:150–162 (1984)CrossRefGoogle Scholar
  13. 13.
    Kim CE: On the celluar convexity of complexes. IEEE Trans Pattern Anal Mach Intell, pp 617–625 (1981)Google Scholar
  14. 14.
    Kung HT: Memory requriements for balanced computer architectures. Proc 13th Annu Int Symp on Computer Architecture, June 1986Google Scholar
  15. 15.
    Kung HT, Webb JA: Mapping image processing operations onto a linear systolic machine. Distrib Comput 1 (1986)Google Scholar
  16. 16.
    Marberg JM, Gafni e: Sorting in constant number of row and column phases on a mesh. Algorithmica 3 (1988)Google Scholar
  17. 17.
    Miller R, Stout QF: Geometric algorithms for digitzed pictures on a mesh-connected computer. IEEE Trans Pattern Anal Mach Intell, March 1985Google Scholar
  18. 18.
    Miller R, Stout QF: Data movement techniques for the pyramid computer. SIAM J Comput 2 (1987)Google Scholar
  19. 19.
    Nassimi D, Sahni S: Finding connected components and connected ones on a mesh-connected parallel computer. SIAM J Comput 9 (4), 1980Google Scholar
  20. 20.
    Nassimi D, Sahni S: Data broadcating in SIMD computers. IEEE Trans Comput C-30, 2, February 1981Google Scholar
  21. 21.
    Prasanna Kumar VK, Eshaghian M: Geometric algorithms for digitized pictures on the mesh of trees organization. Proc IEEE International Conference on Parallel Processing, 1986Google Scholar
  22. 22.
    Preparata F, Shamos MI: Computational Geometry: an Introduction. Springer, Berlin Heidelberg New York, 1985Google Scholar
  23. 23.
    Ramakrishnan IV, Varman PJ: Modular matrix multiplication on a linear array. IEEE Trans Comput C-33, November 1984Google Scholar
  24. 24.
    Rosenfeld A: Parallel image processing using cellular arrays. IEEE Computer v. 16, 1983Google Scholar
  25. 25.
    Ullman J: Computational Aspects of VLSI. Computer Science Press, 1984Google Scholar

Copyright information

© Springer-Verlag 1991

Authors and Affiliations

  • Hussein M. Alnuweiri
    • 1
  • Viktor K. Prasanna
    • 2
  1. 1.Department of Electrical EngineeringUniversity of British ColumbiaVancouverCanada
  2. 2.Department of EE-Systems, EEB-244University of Southern CaliforniaLos AngelesUSA

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